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Association of a Healthy Lifestyle With All-Cause and Cause-Specific Mortality Among Individuals With Probable Sarcopenia: Population-Based Cohort Study

Association of a Healthy Lifestyle With All-Cause and Cause-Specific Mortality Among Individuals With Probable Sarcopenia: Population-Based Cohort Study

Regular physical activity conferred the second-greatest survival benefit in the general population [30], which was consistent with prior reports by Li et al [32]; while dietary quality (HR 0.88, 95% CI 0.82‐0.94 in men; HR 0.97, 95% CI 0.90‐1.05 in women) and excessive alcohol intake (HR 0.95, 95% CI 0.89‐1.01 in men; HR 1.03, 95% CI 0.94‐1.12 in women) had weaker associations with mortality [30].

Ning Wang, Yuqing Zhang, Junqing Xie, Na Lu, Aojie Zheng, Changjun Li, Jie Wei, Chao Zeng, Guanghua Lei, Yilun Wang

JMIR Aging 2025;8:e65374

Developing an Evaluation Index System for Service Capability of Internet Hospitals in China: Mixed Methods Study

Developing an Evaluation Index System for Service Capability of Internet Hospitals in China: Mixed Methods Study

Li and Guo [12] constructed a set of online medical service quality indicators for public hospitals in China from the perspective of online and offline integration. The primary indicators and their weights are outcome quality (0.34), process quality (0.26), structure quality (0.22), and integration quality (0.18). Despite the rapid expansion of internet hospitals, existing evaluation frameworks primarily assess service quality and patient satisfaction.

Mingge Xia, Qi Liu, Li Ma, Jingyu Wen, Yan Xue, Hao Hu, Min Li, Hong Wei

J Med Internet Res 2025;27:e72931

Autoencoder-Based Representation Learning for Similar Patients Retrieval From Electronic Health Records: Comparative Study

Autoencoder-Based Representation Learning for Similar Patients Retrieval From Electronic Health Records: Comparative Study

(A)Vanilla AE;(B)Contractive AE;(C) Denoising AE;(D) Sparse AE; and(E) Robust AE. MCC: maximum correntropy criterion; MSE: mean squared error. Here, X denotes the input data, and X` represents the reconstructed data. Z is the output of the latent representation produced by the encoder. W, W`, b, and b` are the weights and biases of the encoder and decoder, while ϕ1 and ϕ2 are activation functions.

Deyi Li, Aditi Shukla, Sravani Chandaka, Bradley Taylor, Jie Xu, Mei Liu

JMIR Med Inform 2025;13:e68830

Predicting In-Hospital Mortality in Intensive Care Unit Patients Using Causal SurvivalNet With Serum Chloride and Other Causal Factors: Cross-Country Study

Predicting In-Hospital Mortality in Intensive Care Unit Patients Using Causal SurvivalNet With Serum Chloride and Other Causal Factors: Cross-Country Study

Probabilistic principal component analysis was used to impute continuous variables with missing values Patient selection flowcharts for four international cohorts used in this study: (A) MIMIC-IV (N=70,370), (B) e ICU-CRD (N=112,457), (C) Yantai Yuhuangding Hospital affiliated with Qingdao University (N=4653), and (D) Sichuan Zigong Fourth People’s Hospital (N=1982). Detailed inclusion and exclusion criteria are provided in e Text 1 in Multimedia Appendix 1.

Jing Wang, Qixiu Li, Can Xie, Xiaofei Li, Huikao Wang, Wei Xu, Ruyan Lv, Xiaobing Zhai, Ping Xu, Kefeng Li, Xi-Cheng Song

J Med Internet Res 2025;27:e70118

A Weighted Voting Approach for Traditional Chinese Medicine Formula Classification Using Large Language Models: Algorithm Development and Validation Study

A Weighted Voting Approach for Traditional Chinese Medicine Formula Classification Using Large Language Models: Algorithm Development and Validation Study

In equation 1, we have N fine-tuned LLMs, where the predicted value for LLMi is denoted by Ci , N=10, and c represents all classes of the TCM formula. 1(Ci=c) is the indicator function, equal to 1 if Ci=c, and 0 otherwise. The final prediction result yhard is determined by selecting the class with the highest number of votes. In equation 2, αi represents the average accuracy of each LLM, the votes for each LLM are multiplied by the corresponding weights, and the resulting weighted votes are summed.

Zhe Wang, Keqian Li, Suyuan Peng, Lihong Liu, Xiaolin Yang, Keyu Yao, Heinrich Herre, Yan Zhu

JMIR Med Inform 2025;13:e69286